Public preferences for ecological indicators used in Everglades restoration

The Everglades is one of the largest wetland ecosystems in the world covering almost 18,000 square miles from central Florida southward to Florida Bay. Over the 20th century, efforts to drain the Everglades for agriculture and development severely damaged the ecosystem so that today roughly 50% of the historic flow of water through the Everglades has been diverted elsewhere. In an attempt to restore the Everglades, the U.S. Congress authorized the Comprehensive Everglades Restoration Plan (CERP) in 2000, expected to cost over $16 billion and to take several decades to complete. We used the results from a stated preference choice experiment (SPCE) survey of Florida households to estimate the willingness to pay for several ecological attributes related to CERP performance indicators likely to be impacted by Everglades restoration. We also used a latent class model (LCM) to explore preference heterogeneity among respondents. On average, survey respondents were willing to pay for improvements in all of the attributes included in the survey, namely increased populations of wading birds, American alligators, endangered snail kites, and spotted seatrout, and reduced polluted discharges from Lake Okeechobee to the Caloosahatchee and St. Lucie rivers. Willingness to pay was highest for reduced polluted discharges from Lake Okeechobee.Data Availability: All relevant data are available at https://doi.org/10.17605/OSF.IO/9AG7Z.S1 Table. Comparison between the demographics of the survey sample respondents and the Florida population based on 2010 U.S. Census information. https://doi.org/10.1371/journal.pone.0234051.s001S2 Table. Regression results from conditional logit model with willingness to pay estimates. https://doi.org/10.1371/journal.pone.0234051.s002The Everglades Foundationhttp://www.plosone.orghj2020Mammal Research Institut

Quasi-extinction risk and population targets for the Eastern, migratory population of monarch butterflies (Danaus plexippus)

The Eastern, migratory population of monarch butterflies (Danaus plexippus), an iconic North American insect, has declined by ~80% over the last decade. The monarch’s multi-generational migration between overwintering grounds in central Mexico and the summer breeding grounds in the northern U.S. and southern Canada is celebrated in all three countries and creates shared management responsibilities across North America. Here we present a novel Bayesian multivariate auto-regressive state-space model to assess quasi-extinction risk and aid in the establishment of a target population size for monarch conservation planning. We find that, given a range of plausible quasi-extinction thresholds, the population has a substantial probability of quasi-extinction, from 11–57% over 20 years, although uncertainty in these estimates is large. Exceptionally high population stochasticity, declining numbers, and a small current population size act in concert to drive this risk. An approximately 5-fold increase of the monarch population size (relative to the winter of 2014–15) is necessary to halve the current risk of quasi-extinction across all thresholds considered. Conserving the monarch migration thus requires active management to reverse population declines, and the establishment of an ambitious target population size goal to buffer against future environmentally driven variability

Density estimates of monarch butterflies overwintering in central Mexico

Given the rapid population decline and recent petition for listing of the monarch butterfly (Danaus plexippus L.) under the Endangered Species Act, an accurate estimate of the Eastern, migratory population size is needed. Because of difficulty in counting individual monarchs, the number of hectares occupied by monarchs in the overwintering area is commonly used as a proxy for population size, which is then multiplied by the density of individuals per hectare to estimate population size. There is, however, considerable variation in published estimates of overwintering density, ranging from 6.9–60.9 million ha−1. We develop a probability distribution for overwinter density of monarch butterflies from six published density estimates. The mean density among the mixture of the six published estimates was ∼27.9 million butterflies ha−1 (95% CI [2.4–80.7] million ha−1); the mixture distribution is approximately log-normal, and as such is better represented by the median (21.1 million butterflies ha−1). Based upon assumptions regarding the number of milkweed needed to support monarchs, the amount of milkweed (Asclepias spp.) lost (0.86 billion stems) in the northern US plus the amount of milkweed remaining (1.34 billion stems), we estimate >1.8 billion stems is needed to return monarchs to an average population size of 6 ha. Considerable uncertainty exists in this required amount of milkweed because of the considerable uncertainty occurring in overwinter density estimates. Nevertheless, the estimate is on the same order as other published estimates. The studies included in our synthesis differ substantially by year, location, method, and measures of precision. A better understanding of the factors influencing overwintering density across space and time would be valuable for increasing the precision of conservation recommendations

A General Modeling Framework for Describing Spatially Structured Population Dynamics

Variation in movement across time and space fundamentally shapes the abundance and distribution of populations. Although a variety of approaches model structured population dynamics, they are limited to specific types of spatially structured populations and lack a unifying framework. Here, we propose a unified network‐based framework sufficiently novel in its flexibility to capture a wide variety of spatiotemporal processes including metapopulations and a range of migratory patterns. It can accommodate different kinds of age structures, forms of population growth, dispersal, nomadism and migration, and alternative life‐history strategies. Our objective was to link three general elements common to all spatially structured populations (space, time and movement) under a single mathematical framework. To do this, we adopt a network modeling approach. The spatial structure of a population is represented by a weighted and directed network. Each node and each edge has a set of attributes which vary through time. The dynamics of our network‐based population is modeled with discrete time steps. Using both theoretical and real‐world examples, we show how common elements recur across species with disparate movement strategies and how they can be combined under a unified mathematical framework. We illustrate how metapopulations, various migratory patterns, and nomadism can be represented with this modeling approach. We also apply our network‐based framework to four organisms spanning a wide range of life histories, movement patterns, and carrying capacities. General computer code to implement our framework is provided, which can be applied to almost any spatially structured population. This framework contributes to our theoretical understanding of population dynamics and has practical management applications, including understanding the impact of perturbations on population size, distribution, and movement patterns. By working within a common framework, there is less chance that comparative analyses are colored by model details rather than general principles

Conservation relevance of bat caves for biodiversity and ecosystem services

All ecosystems are dotted by salient small natural features that not only characterize them but also significantly add to their biodiversity and functions. These small natural features are prominent but easily missed when ecosystems are described. Caves are one key example of this. Cave ecosystems are underrepresented in conservation planning and implementation around the world and have become mostly overlooked in conservation strategies overall. Caves contain high levels of biodiversity from fungi to invertebrates to vertebrates. This paper emphasizes bat caves as providers of ecosystem services to vast areas surrounding them, in the order of hundreds of thousands of square km just in North America. Their influence extends three-dimensionally via subterraneous water bodies and via the aerial nightly dispersal of the bats that provide a host of services from seed dispersal to pollination to pest control. The examples used focus primarily on free-tailed bats in North America, but the same principles apply to any other cave in the world with significant bat colonies. Caves enjoy protection, legal or actual, in some countries and not in others, and as a result many have suffered damage or been destroyed altogether. Common threats are vandalism, urbanization, and pollution. Many caves are attractive as ecotourism destinations and provide unique opportunities to educate the public about unexpected biodiversity values and ecosystem services. Inventorying caves poses challenges, but efforts are under way to assess caves in need of protection. Incipient cave protection strategies include legal and educational efforts, and management. Although illustrated with bat caves, given the importance of all caves and their precarious status, it is time to call the attention of decision makers about the urgent need to launch a worldwide cave conservation initiative

Multilayer Feedforward Artificial Neural Network Model to Forecast Florida Bay Salinity with Climate Change

Florida Bay is a large, subtropical estuary whose salinity varies from yearly and seasonal changes in rainfall and freshwater inflows. Water management changes during the 20th century led to a long-term reduction in inflows that increased mean salinity, and the frequency and severity of hypersalinity. Climate change may exacerbate salinity conditions in Florida Bay; however, future salinity conditions have not been adequately evaluated. Here, we employed a Multilayer Feedforward Artificial Neural Network model to develop baseline salinity models for nearshore and offshore sites. Then, we examined the impacts of climate change on salinity using forecasted changes in various input variables under two climate change scenarios, representative concentration pathways (RCP) 4.5 and 8.5. Salinity could rise by 30% and 70% under the RCP4.5 and RCP8.5 forecasts, respectively. Climate change affected nearshore salinity significantly more, which rapidly fluctuated between mesohaline (5 to 18 PSU) and metahaline (40 to 55 PSU) to hypersaline conditions (>55 PSU). Offshore salinities ranged between euhaline (30 to 40 PSU) to metahaline (40 to 55 PSU) conditions. Our study suggests that increased freshwater flow would help maintain suitable estuarine conditions in Florida Bay during climate change, while our novel modeling approach can guide further Everglades restoration efforts

Public preferences for ecological indicators used in Everglades restoration.

The Everglades is one of the largest wetland ecosystems in the world covering almost 18,000 square miles from central Florida southward to Florida Bay. Over the 20th century, efforts to drain the Everglades for agriculture and development severely damaged the ecosystem so that today roughly 50% of the historic flow of water through the Everglades has been diverted elsewhere. In an attempt to restore the Everglades, the U.S. Congress authorized the Comprehensive Everglades Restoration Plan (CERP) in 2000, expected to cost over $16 billion and to take several decades to complete. We used the results from a stated preference choice experiment (SPCE) survey of Florida households to estimate the willingness to pay for several ecological attributes related to CERP performance indicators likely to be impacted by Everglades restoration. We also used a latent class model (LCM) to explore preference heterogeneity among respondents. On average, survey respondents were willing to pay for improvements in all of the attributes included in the survey, namely increased populations of wading birds, American alligators, endangered snail kites, and spotted seatrout, and reduced polluted discharges from Lake Okeechobee to the Caloosahatchee and St. Lucie rivers. Willingness to pay was highest for reduced polluted discharges from Lake Okeechobee

Watershed Response to Legacy Phosphorus and Best Management Practices in an Impacted Agricultural Watershed in Florida, U.S.A.

Soil phosphorus (P) built up due to past management practices, legacy P, in the Lake Okeechobee Watershed (LOW) in south-central Florida, U.S.A., is often discussed as the root cause of lake eutrophication. Improvement of the lake’s water quality requires the identification of critical P sources and quantifying their contributions. We performed a global sensitivity analysis of the Watershed Assessment Model (WAM), a common evaluation tool in LOW environmental planning, using the Morris method. A pre-calibrated WAM setup (Baseline) of the LOW sub-watershed, Taylor Creek Nubbin Slough (TCNS), was used as a test case. Eight scenarios were formulated to estimate the contributions of various P sources. The Morris analysis indicated that total phosphorus (TP) loads were highly sensitive to legacy P in improved pastures, the major land use covering 46.2% of TCNS. The scenario modeling revealed that legacy P, inorganic fertilizers, and other sources contribute 63%, 10%, and 32%, respectively, to the Baseline TP load of 111.3 metric tons/y to the lake. Improved pastures, dairies, citrus, and field crops are the top TP load contributors. Our results have important implications for water quality improvement plans in the LOW and highlighted the need for accurate spatial mapping of legacy P and incorporation of such information in modeling efforts for watersheds demonstrating legacy P problems

Tropical warming and the dynamics of endangered primates

Many primate species are severely threatened, but little is known about the effects of global warming and the associated intensification of El Niño events on primate populations. Here, we document the influences of the El Niño southern oscillation (ENSO) and hemispheric climatic variability on the population dynamics of four genera of ateline (neotropical, large-bodied) primates. All ateline genera experienced either an immediate or a lagged negative effect of El Niño events. ENSO events were also found to influence primate resource levels through neotropical arboreal phenology. Furthermore, frugivorous primates showed a high degree of interspecific population synchrony over large scales across Central and South America attributable to the recent trends in large-scale climate. These results highlight the role of large-scale climatic variation and trends in ateline primate population dynamics, and emphasize that global warming could pose additional threats to the persistence of multiple species of endangered primates

National valuation of monarch butterflies indicates an untapped potential for incentive-based conservation

The annual migration of monarch butterflies (Danaus plexippus) has high cultural value and recent surveys indicate monarch populations are declining. Protecting migratory species is complex because they cross international borders and depend on multiple regions. Understanding how much, and where, humans place value on migratory species can facilitate market-based conservation approaches. We performed a contingent valuation study of monarchs to understand the potential for such approaches to fund monarch conservation. The survey asked U.S. respondents about the money they would spend, or have spent, growing monarch-friendly plants, and the amount they would donate to monarch conservation organizations. Combining planting payments and donations, the survey indicated U.S. households valued monarchs as a total one-time payment of $4.78–$6.64 billion, levels similar to many endangered vertebrate species. The financial contribution of even a small percentage of households through purchases or donations could generate new funding for monarch conservation through market-based approaches